Analytics Engineer

Higharc•Remote, Remote

16d•Remote

About The Position

Higharc is seeking an expert Analytics Engineer to own how data is structured, understood, and surfaced across our platform for the builders who use our product and for the Product and Customer Success teams who depend on their own internal analytics. This is a net-new role on the Software Engineering team, created because our largest customers are asking harder analytics questions than anyone currently owns.

Requirements

6+ years in analytics, data science, or business intelligence, owning work end-to-end from modeling through presentation
Proven expertise writing and optimizing SQL in a business context, with strong data modeling fundamentals
Hands-on experience with a BI/visualization tool such as Looker or Observable
Experience with data warehouses and pipelines (BigQuery, S3, or equivalent) and product analytics tools (PostHog or similar)
A track record building both internal and customer-facing dashboards and reporting
Strong ability to manage fast-paced, ambiguous projects with a high degree of organization and independence
Sharp judgment about what data belongs in front of which audience

Nice To Haves

Experience delivering analytics to large enterprise customers with their own reporting requirements
Background in construction tech, homebuilding, or another complex physical-world domain

Responsibilities

Design, build, and maintain scalable data models and views in Looker/Observable that serve both customer-facing and internal analytics
Partner with engineering to design and ship polished customer-facing data views for enterprise builders
Work with Product and Customer Success to define the metrics they need to make decisions, then build the reporting behind them
Set direction for our analytics stack and decide where each piece of reporting should live
Own decisions about data infrastructure and instrumentation, including how data flows between systems like BigQuery and S3, and where product analytics tracking such as PostHog needs to change
Use data modeling, statistics, and analytical techniques to identify trends, patterns, and anomalies across large datasets
Build a triage process for incoming analytics requests across the org so priorities are clear and the queue doesn't run you
Serve as the clear, trusted owner of "what the data says"